Muscle State Estimation via Multi-Sensor Fusion
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Solution Overview
Problem
Existing technologies are unable to accurately estimate the state of muscles, including muscle usage, grip strength, and muscle strength, as they rely on incomplete or inaccurate measurements of muscle circumference and myoelectric potentials.
Innovation Solution
A muscle state estimation device and method that combines circumference measurement with myopotential and motion state measurement, using evaluation functions to minimize deviations from established models, and incorporates machine learning to construct probability models for accurate muscle state calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional measurement methods (circumference or myoelectric potential alone) are used, then the measurement process is simple, but the muscle state estimation accuracy is insufficient
Solution Approach 1:
The patent combines multiple measurement methods (circumference measurement, myoelectric potential measurement, and motion state measurement) into a single integrated system. The muscle state estimation unit synthesizes data from all three measurement sources to calculate comprehensive muscle state parameters, thereby improving estimation accuracy while managing system complexity through unified processing.
2Measurement precision
If multiple measurement methods are combined to improve accuracy, then the muscle state estimation accuracy improves, but the device complexity increases
Solution Approach 1:
The muscle state estimation unit serves multiple functions by processing data from different measurement sources (circumference, myoelectric potential, motion state) and calculating various muscle state parameters (muscle tension, co-contraction, weakness). This multi-functional approach allows the system to achieve comprehensive muscle state assessment without requiring separate dedicated processing units for each measurement type.
Solution Approach 2:
The system uses an evaluation function that calculates deviations between measured values and model-predicted values, then minimizes these deviations through optimization. This feedback mechanism continuously adjusts the muscle state calculations based on the consistency between multiple measurement sources and established models, improving accuracy while providing a systematic framework for integrating complex measurements.
3Measurement precision
If evaluation functions with multiple variables are used to minimize deviations from models, then the muscle state calculation accuracy improves, but the computational complexity increases
Solution Approach 1:
The system calculates muscle state parameters that are sufficient for practical application purposes rather than attempting to compute every possible muscle parameter. The evaluation function focuses on minimizing deviations for the most critical muscle state indicators (tension, co-contraction, weakness), providing adequate accuracy for rehabilitation and training applications without requiring exhaustive computational analysis of all muscle parameters.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables precise estimation of muscle state, including muscle tension, co-contraction, and weakness, providing quantitative assessment of both active and passive muscle deformations, thereby overcoming the limitations of conventional methods.
Implementation Method 1
a myopotential measuring means that measures the electric potential generated by the activity of the muscle
Data Source
AI summary
An apparatus and method capable of accurately estimating a participant's muscle state are provided. In order to solve this problem, a muscle state estimation device 1 for estimating the state of a participant's muscles is provided. The muscle state estimation device 1 comprises a circumference sensor 2 that measures the circumference of the muscle, a myopotential sensor 3 that measures the electric potential generated by the activity of the muscle and a muscle state estimation unit 4 that calculates the muscle state such that an evaluation function, of which variables are the deviation of the circumference measured by the circumference sensor 2 from the circumference model that defines the relationship between the muscle state and the circumference and the deviation of the electric potential measured by the myopotential sensor 3 from the muscle tension model that defines the relationship between the muscle state and the electric potential, is minimized.